Influence Of Climate Variability Research Articles

What is the probability that a drought will break in Australia?

Large scale modes of climate variability influence rainfall and soil moisture in southeastern Australia, and extended dry conditions have been associated with a lack of climate mode phases conducive to wetter conditions. However, the role of large-scale climate variability in breaking ongoing soil moisture droughts has not been well quantified, and the utility of large-scale signals in drought recovery assessments have not been explored. Here, we study the influence of El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on the probability of soil moisture drought breaking in eastern and southeastern Australia, using logistic regression modelling. A long-term historical dataset from the Australian Water Resources Assessment Landscape (AWRA-L) model is used for the assessment. The probability estimates from the logistic regression modelling validate well against observed probability of a drought ending. We then use model estimates to understand the probability contributions from different climate modes. We show that there is a seasonal pattern in soil moisture drought breaking probabilities with higher probabilities in austral summer in eastern Australia and summer/autumn in southeastern Australia. ENSO has the largest influence on probabilities in winter with extreme opposite phases of the mode resulting in regional average probability differences of 15–26%. The IOD exhibits the largest influences during spring and winter and opposite phases result in differences of about 18%. The method can be used to estimate soil moisture drought breaking probabilities in near real-time during drought events, and may assist decision making by managers engaged in drought risk and water resources planning.

Asymmetries in climate change and livestock productivity: non-linear evidence from autoregressive distribution lag mode

IntroductionThe livestock sector is extremely important to Socioeconomic growth in Pakistan, yet it is also quite vulnerable to weather changes. Climate change reduces livestock production by changing ecosystem services such as water availability, feed quality and quantity, disease outbreaks, animal heat stress, and a decline in livestock variety and breeds. Climate change has a direct impact on ecological and animal health. As a consequence of climate change, animal diseases, and infections are becoming more widespread. With the non-linearities of climate change in the livestock industry in mind, the present study investigated the asymmetric influence of climatic and non-climatic variables on livestock productivity across Pakistan. The empirical analysis was conducted utilizing secondary time series data from 1980 to 2021.MethodThe non-linear autoregressive distributive lag (NARDL) model is used to examine the asymmetric behavior of climatic variability in the livestock sector. We included CO2 emissions, mean temperature (MT), and precipitation (PERC) as climatic variables in the current study, along with additional control factors.Results and discussionOur research discovered that CO2, MT, and PREC had asymmetries in their impacts on livestock. Variations in CO2, MT, and PREC have contradictory effects on livestock productivity in the long and short term. A percent increase in LCO2 leads to a fall in livestock production insignificantly by 1.0062% for Model I and significantly by 5.7613% and 5.3929% for Models II and III, respectively. A percent decrease in LCO2 significantly lowers livestock production by 4.1739% for Model I and improves livestock production by 8.5928% and 6.7901%, respectively, for Model II and Model III. A unit increase in MT significantly improves livestock productivity by 1.5520% and 0.8149% for Models II and III, respectively, while a unit decrease in MT insignificantly improves livestock production by 0.1316% and 0.2122% for Models II and III, respectively. A unit increase and decrease in PREC significantly lowers and insignificantly improve livestock productivity respectively by 0.002% in both cases for Model III. To protect the livestock industry from the negative effects of climate change, this study suggests that livestock producers use new environmentally friendly technologies and ecological agricultural systems.

Complicating Cultural Reproduction Theory: A Critical Multilevel Analysis of Systematic Inequality in U.S. Schools

The purpose of the current study is to examine malleable school practices and norms that contribute to inequitable school learning environments based on student background. Using multilevel structural equation modeling (SEM) with the U.S. sample of PISA 2015, this study examines the extent to which student-level access to inquiry-based science learning opportunities and academic press mediates the relationship between intersectional student background and scientific literacy outcomes, as well as the influence of school-level context, tracking, and academic climate variables on student learning opportunities, perceptions of academic press, and science outcomes. After accounting for variance explained at the school level, OTL was not a significant mediator of the relationship between student intersectional background or gender and scientific literacy outcomes. However, academic press was a significant mediator at the student level, and was a significant negative predictor of science achievement. At the school level, while tracking was not a significant predictor of mean school science achievement, tracking was a predictor of mean school academic press and OTL inquiry-based science. There were significant differences in school academic climate based on school context, and school-level perceptions of academic climate were significant predictors of science achievement, findings that can inform education policy and practice.

Influences of Ecological Restoration Programs on Ecosystem Services in Sandy Areas, Northern China

Ecosystem services (ESs) are important for supporting human development. However, a changing climate and anthropogenic impacts are resulting in the degradation of dryland ecosystems to varying degrees. While there has been the global implementation of Ecological Restoration Programs (ERPs) to restore degraded ecosystems, there remains limited comprehensive assessment of their impacts on ESs of drylands. In this study, the sandy areas of northern China were used as the study area. The RUSLE, RWEQ, CASA, and InVEST models were used to simulate four major ESs: soil conservation (SC), sand fixation (SF), carbon sequestration (CS), and water yield (WY). The study aimed to evaluate the influences of various ERPs on major ESs. The dominant factors affecting the overall benefits provided by ESs were also identified. Since ERPs were implemented, forest areas have increased by 2.8 × 104 km2, whereas the areas of cropland, shrubland, and grassland have decreased. There were generally increasing trends in SF, SC, and CS, whereas there was a decreasing trend in WY. We then used a scenario-based simulation approach to eliminate the influence of climate variability on ESs. The results showed increasing trends in SF, SC, and CS, whereas there were minimal changes in WY. The results suggested that although ERPs can significantly increase regional ESs, unregulated expansion in vegetation can result in a water crisis and affect regional water security.

Detecting the long-term spatiotemporal crop phenology changes in a highly fragmented agricultural landscape

Trends in crop phenometrics reveal the influence of climate variability and change on crop growth and development. However, the trends are less clear in fragmented tropical smallholder landscapes, because there is high spatial and temporal variability in crop phenology. Frequent historical and high spatial resolution (≤30 m) Earth observations are needed to track changes in crop phenology in fragmented landscapes but are often unavailable. The spatial–temporal gap can be closed by integrating infrequent high spatial resolution Earth observations with low spatial/high temporal resolution observations through data fusion. We fused 30 m resolution Landsat and 250 m resolution MODIS imagery to investigate trends in crop phenology from 2000 to 2020 in a fragmented agricultural landscape of Ethiopia. We used the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) that had recently been modified for application in fragmented agricultural landscapes. We used the non-parametric Mann–Kendall test for crop phenology trend analysis. Crop phenology based on Landsat–MODIS fusion was compared to MODIS-based crop phenology without fusion. We found data fusion yielded a smaller magnitude of changes in the start of season (SOS: -0.2-day-y−1) and end of season (EOS: -0.50-day-y−1) compared to MODIS SOS (-0.5-day-y−1) and EOS (1.38-day-y−1) due to MODIS-related mixing with the surrounding natural vegetation in the fragmented agricultural landscape. EOS showed a faster rate of change compared to SOS over the 21-years. The Landsat and MODIS fusion captured spatial variation in the timing and magnitude of change specific to crops and their growing environment, which has implications for adaptation strategies. Our results highlight the importance of long-term data fusion to improve the spatial dimension of crop phenology time series analysis. Integrating time series land cover maps into the data fusion processing chain could further improve long-term data fusion for crop phenology trend analysis.

Rates of Stemwood Carbon Accumulation Are Linked to Hydroclimate Variability in Mexican Conifers

Evapotranspiration demand has increased rapidly as temperatures have risen, affecting forest productivity. Consequently, carbon (C) uptake by forests is being modified; therefore, a more refined knowledge of the relationships between C capture and hydroclimate variability is required, particularly in drought-prone regions. In this study, we analyzed the relationships between climate and C capture as stemwood through the dendroecological analyses of radial growth in 15 conifer species distributed along a broad bioclimatic gradient in Mexico. The C content was calculated using densitometry data; correlations and mixed models were then used to determine the influence of climatic variables (precipitation, mean maximum and minimum temperatures, SPEI drought index) on tree growth. Each species showed specific responses to the climate with Taxodium mucronatum being the most responsive species. Both precipitation and maximum temperature best explained changes in C capture, with minimum temperature and SPEI playing secondary roles. The winter before the growth period was the most important season for C capture, particularly through positive responses to wet-cool conditions. However, the climatic influences of the current fall and summer were also notable. Seasonal climatic influences have implications for C uptake and forest productivity in the face of the severe droughts that repeatedly affect the study region.

Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (−0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = −0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Impact of climate factors and climate-gene interaction on systemic lupus erythematosus patients' response to glucocorticoids therapy.

Glucocorticoids (GCs) were the essential drugs for systemic lupus erythematosus (SLE). However, different patients differ substantially in their response to GCs treatment. Our current study aims at investigating whether climate variability and climate-gene interaction influence SLE patients' response to the therapy of GCs. In total, 778 SLE patients received therapy of GCs for a study of 12-week follow-up. The efficacy of GCs treatment was evaluated using the Systemic Lupus Erythematosus Disease Activity Index. The climatic data were provided by China Meteorological Data Service Center. Additive and multiplicative interactions were examined. Compared with patients with autumn onset, the efficacy of GCs in patients with winter onset is relatively poor (ORadj = 1.805, 95%CIadj : 1.181-3.014, padj = 0.020). High mean relative humidity during treatment decreased the efficacy of GCs (ORadj = 1.033, 95%CIadj : 1.008-1.058, padj = 0.011), especially in female (ORadj = 1.039, 95%CIadj : 1.012-1.067, padj = 0.004). There was a significant interaction between sunshine during treatment and TRAP1 gene rs12597773 on GCs efficacy (Recessive model: AP = 0.770). No evidence of significant interaction was found between climate factors and the GR gene polymorphism on the improved GCs efficacy in the additive model. Multiplicative interaction was found between humidity in the month prior to treatment and GR gene rs4912905 on GCs efficacy (Dominant model: OR = 0.470, 95%CI: 0.244-0.905, p = 0.024). Our findings suggest that climate variability influences SLE patients' response to the therapy of GCs. Interactions between climate and TRAP1/GR gene polymorphisms were related to GCs efficacy. The results guide the individualized treatment of SLE patients.

Assessment of Land Cover Changes and Climate Variability Effects on Catchment Hydrology Using a Physically Distributed Model

Land use/land cover, along with climate variability, play vital roles in hydrological functionality of catchments and are leading threats to inter-related hydrological processes. In the current study, a physically distributed Soil and Water Assessment Tool model is used to investigate the impact of historical changes on the hydrologic response of the Damodar catchment (Jharkhand, India) in terms of inflow to the Panchet reservoir. The model was validated for the monthly runoff and inflow at the outlets of four watersheds and three reservoirs in the Damodar catchment before the assessment of changes in inflow at the Panchet reservoir was performed. The analysis of land cover thematic maps prepared using satellite images of Landsat 4, 5 and 7 showed that from 1972 to 2001, the land cover in the Damodar catchment changed considerably. The interpretation of land cover results indicates that significant increases in settlements (140%), waterbodies (98.42%) and agricultural land (26.71%), along with decreases in wasteland (32.63%) and forest (15.28%), occurred due to development. The Mann–Kendall test was used for measuring the rainfall and temperature for the Damodar catchment, which showed that this region became drier during 1970–2005, with decreases in the annual rainfall and increases in the mean temperature. A simulated hydrological impact under land cover dynamics and climate variability in the historical time frame of 1970–2000 using the model revealed a gradual increase of 26.16% in the Panchet reservoir inflow. The study revealed that the increased inflow is relatively greater under the influence of climate variability due to changes in rainfall and temperature, rather than land cover, that were observed over the region.

The inclusion of immediate and lagged climate responses amplifies the effect of climate autocorrelation on long‐term growth rate of populations

Abstract Climate variability will increase with climate change, and thus it is important for population ecologists to understand its consequences for population dynamics. Four components are known to mediate the consequences of climate variability: the magnitude of climate variability, the effect size of climate on vital rates, covariance between vital rates and autocorrelation in climate. Recent studies have pointed to a potential fifth component: vital rates responding to climate in different timeframes, with some responding more immediately and some having lagged responses. We use simulations to quantify how all five components modify the consequences of climatic variability on long‐term population growth rates across a range of life histories defined by life expectancy and iteroparity. We use an established method to compose Matrix Population Models for 147 life histories. Our simulations show that including different timeframes for vital rates responses to climate can either reduce or amplify the negative influence of climate variability on long‐term population growth rates. The negative effect of different timeframes for vital rates responses on population growth is amplified when climatic autocorrelations are negative, and when species are long‐lived. Synthesis. The existing literature shows that vital rates often respond to climate in different timeframes, and that studies often ignore climate autocorrelation. Our results show that simultaneously including both of these factors can substantially increase or decrease a population's expected growth rate. Moreover, the relative magnitude of this change increases with the generation time of a life history. Our results are relevant to conservation, population forecasts and population modelling in general.

Job Satisfaction of Vocational High School Teachers

The purpose of this study is to analyze the relationship between: 1) organizational climate with teacher job satisfaction, 2) commitment with teacher job satisfaction and 3) climate and commitment together with teacher job satisfaction. The research was conducted at SMK in Ciracas District, East Jakarta with a population of 362 teachers. Using the Slovin formula with an error rate of 0.05, a simple random sample of 191 teachers was taken. Test the hypothesis using a correlation test. For the measurement of job satisfaction variables, five dimensions are used: namely interest in work done with indicators (1) diligent work and (2) increasing competence. The dimensions of awards received with indicators (1) compensation and (2) promotion. The supervisor's ability dimension provides technical assistance with indicators: (1) academic supervision and (2) clinical supervision. In general, the results of the study prove that the job satisfaction of teachers working at SMK Ciracas District can be influenced by organizational climate variables and commitment variables. As for suggestions for research related to the integration model of the influence of organizational climate variables and organizational commitment to job satisfaction, it can be done in the scope of work of private organizations.

Impact of Climate Variability on Rainfall Characteristics in the Semi-Arid Shashe Catchment (Botswana) from 1981–2050

Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catchments that are highly variable and are not well explored. In this study, we explore the influence of climate variability on the spatial distribution and rainfall characteristics at a local scale in the semi-arid Shashe catchment, Northeastern Botswana. The LARS-WG, Long Ashton Research Station Weather Generator downscaling method, three representative scenarios (RCP 2.6, RCP 4.5, and RCP 4.5), three trend detection methods (Mann-Kendall, Sen’s slope, and innovative trend analysis) and L-moment method were used to assess climate change impacts on rainfall. Two data sets were used; one with 40 years of observed data from 1981–2020 and the other with 70 years from 1981–2050 (40 years of observed and 30 years of projected data from 2021–2050). Generally, the study found trend inconsistencies for all the trend detection methods. In most cases, Sen’s Slope has a high estimate of observed and RCP 2.6, while ITA overestimates rainfall totals under RCP 4.5 and RCP 8.5. The trend is increasing for annual total rainfall in most gauging stations while decreasing for annual maximum rainfall. The catchment is homogeneous, and Generalized Logistic distribution is the dataset’s best-fit distribution. Spatial coverage of a 100-year rainfall between 151–180 mm will be 81% based on observed data and 87% based on projected data under RCP 2.6 scenario when it happens. A 200-year rainfall between 196–240 mm under RCP 4.5 and 8.5 has high spatial areal coverage, at least 90% of the total catchment. The outcomes of this study will provide insightful information for water resource management and flood risk assessment under climate change. There is a need, however, to assess the transferability of this approach to other catchments in the country and assess the performance of other advanced modelling systems, such as machine learning, in this region.

Evaluation of water-land resources regulation potential in the Yiluo River Basin, China

Our study was designed to spatially assess the regulation potential of watershed water-land resources, and determine its regulation objectives for subsequent optimal allocation. We centred around the Yiluo River Basin, being a soil conservation demonstration plot in the middle course of the Yellow River Basin. In accordance with the criteria of the green development, the high efficiency and the safety, the evaluation system of water-land resources regulation potential was established. Then the fuzzy comprehensive evaluation method was applied to assess the watershed water-land resources during 2001–2020 and 2030–2050, and the evaluation results were represented by the eigenvalue T. The research findings pointed out that the assessment grade of watershed water-land resources was mainly moderate and better state, and presented significant spatial agglomeration features in the historical and forecast years. In the context of dual influences of climatic variation and water-land resources exploitation, the assessment eigenvalue T of watershed water-land resources increased by 6% in the historical periods, and decreased by 4.57 ∼ 7.74% in the future periods. Based on the assessment results, it was recommended to restrict the water-land resources exploitation in the upstream, control the soil erosion in the midstream, and coordinate the relationship between the exploitation and protection of water-land resources in the lower reaches. Our study offers scientific evidence for the elaborate regulation of watershed water-land resources.

Survival rates in the world's southernmost forest bird community.

The Magellanic sub-Antarctic Forest is home to the world's southernmost avian community and is the only Southern Hemisphere analogue to Northern Hemisphere temperate forests at this latitude. This region is considered among the few remaining pristine areas of the world, and shifts in environmental conditions are predominantly driven by climate variability. Thus, understanding climate-driven demographic processes is critical for addressing conservation issues in this system under future climate change scenarios. Here, we describe annual survival patterns and their association with climate variables using a 20-year mark-recapture data set of five forest bird species in the Cape Horn Biosphere Reserve. We develop a multispecies hierarchical survival model to jointly explore age-dependent survival probabilities at the community and species levels in a group of five forest passerines. At the community level, we assess the association of migratory behavior and body size with survival, and at the species level, we investigate the influence of local and regional climatic variables on temporal variations of survival. We found a positive effect of precipitation and a negative effect of El Niño Southern Oscillation on juvenile survival in the white-crested Elaenia and a consistent but uncertain negative effect of temperature on survival in juveniles and 80% of adults. We found only a weak association of climate variables with survival across species in the community and no temporal trends in survival for any of the species in either age class, highlighting apparent stability in these high austral latitude forests. Finally, our findings provide an important resource of survival probabilities, a necessary input for assessing potential impacts of global climate change in this unique region of the world.

Climate Variability and Development Interventions Influence Migration Aspirations and Capabilities of Project Beneficiaries in Southern Ethiopia

In recent years, the European Union (EU) and other donors have increasingly instrumentalised their development cooperation to meet their own domestic migration policy goals, under the assumption that different development interventions—such as building climate resilience – may result in less outward migration from the recipient country. However, it is not yet understood how increased climate resilience would influence individual migration aspirations and capabilities. We conducted 32 in-depth interviews (IDI) and eight focus group discussions (FGD) with beneficiaries of the EU RESET Plus climate-resilience building project in southern Ethiopia. Half of the respondents are adult direct beneficiaries, and the other half are indirect beneficiaries (youths 17–24 years old). By applying a modified aspirations-capabilities framework, we extended the migration-development nexus to climate change and climate-resilience building. We found that climate change worsened perceived conditions and prospects for the future, while the development intervention mostly reinforced already emerging migration aspirations. By improving agricultural output in the context of climate variability, the RESET Plus project contributed to supporting people who wanted to stay to actually be able to do so but also encouraging those wanting to leave by slightly increasing migration capabilities.

Study of the Influence of Climate Variability on the Operation of Wind Farms on the Territory of Russia

Study of the Influence of Climate Variability on the Operation of Wind Farms on the Territory of Russia

Assessment of Crop Weather Relations in Wheat (Triticum aestivum) in Western Maharashtra Plain Zone

Wheat (Triticum aestivum L.) is a thermo-sensitive long-day crop. Temperature is a major determinant of its growth and productivity. Late sown wheat exposes preanthesis phenological events to high temperature that influence grain development and ultimately the yield [1]. Comprehensive assessments of the influence of climate variability on crop yields at local and regional scales can be highly beneficial. With an aim to assess the weather influences on wheat at local scale this study was taken up. An experiment was conducted at Department of Agricultural Meteorology Farm, College of Agriculture, Pune, Maharashtra State (India) in a split-plot design with three replications and sixteen treatment combinations of four different varieties and four sowing windows. Four varieties used were NIAW-301 (Trymbak ), NIAW-917 (Tapovan), NIAW-1415 (Netravati) and NIAW-1994 (Phule Samadhan). Four sowings were taken up on 43rd MW (22-28 October), 45th MW (5-11November), 47th MW (19-25 November) and 49th MW (3-9 December). The grain yield of wheat was influenced significantly by wheat varieties. The grain yields were significantly higher in NIAW-1994 (51.07 and 48.52 qha-1) and significantly superior to the rest of the wheat varieties. This was followed by NIAW-917(45.72 and 43.43qha-1), NIAW-301(43.57 and 41.27 q ha-1). The variety NIAW-1415 recorded significantly lower grain yield (40.89 and 38.84 qha-1) during 2016 and 2017, respectively. Correlation analysis with weather parameters e.g. Temperature (Maximum and Minimum), Relative humidity (Morning and Evening), Rainfall and bright sunshine hours and yield showed that from tillering to 50% flowering stage, maximum temperature (-0.962*) was significantly negatively correlated with grain yield (r = -0.980**), (r =-0.950**) during 2016 and 2017, respectively in NIAW-301 (Trymbak ). The same trend was observed in the remaining varieties also. Regression equations were developed to predict the yield.

Controlling factor analysis of oceanic surface pCO2 in the South China Sea using a three-dimensional high-resolution biogeochemical model

The oceanic surface pressure of CO2 (pCO2) is an essential parameter for understanding the global and regional carbon cycle and the oceanic carbon uptake capacity. We constructed a three-dimensional physical-biogeochemical model with a high resolution of 1/30° for the South China Sea (SCS) to compensate for the limited temporal coverage and limited spatial resolution of the observations and numerical models. The model simulated oceanic surface pCO2 from 1992 to 2021, and the empirical orthogonal function analysis (EOF) of the model results is conducted for a better understanding of the seasonal and interannual variations of oceanic surface pCO2 in this region. The model results showed that the SCS serves as an atmospheric CO2 source from March to October and a sink from November to February, with a domain-averaged climatological oceanic surface pCO2 value that varies between 357 and 408 μatm, and the temporal variation was positively correlated with the variation of sea surface temperature (SST). The majority of the SCS showed a long-term increasing trend for oceanic surface pCO2 with a value of (1.19±0.60) μatm/a, which is in response to the continuously rising atmospheric CO2 concentration. The first EOF mode is positively correlated with the Niño 3 index with a correlation coefficient of 0.51 when the Niño 3 leads 5 months, and the second EOF mode is correlated with the PDO index when the PDO leads 7 months, which suggests an influence of climate variability on the carbonate system. Moreover, it was found that the long-term trend rate of oceanic surface pCO2 was mainly controlled by total CO2 (TCO2) through the decomposition of influence factors, and SST variation took a dominant role in seasonal variations of pCO2. With rapid global warming and continuous release of CO2, the carbonate system in the SCS may change leading to calcite and aragonite saturation.

Impact of climate change on paddy crop failure under different water regimes in Sri Lanka

This study highlighted the severity of paddy harvest failure under various water regimes by elaborating on spatiotemporal variations, and estimating the influence of climatic variation on such crop failure in Sri Lanka. A panel data set obtained from 18 districts from 1981 to 2019 was analysed. The Unharvest Index (UI) (i.e., an index that was developed to measure the intensity of crop failure) was estimated according to seasonal water regimes for each district. The panel data regression method was used for analysis. On average, 5 per cent of areas planted for paddy was unharvested annually, fluctuating with the coefficient of variation at 60 per cent with remarkable spatial variation. Harvest failure was more prominent in rainfed production as compared to irrigated cultivation; in dry and intermediate zones as opposed to wet zones; and in the Maha season (October to March) rather than the Yala season (April to September). Climate variability during the crop season significantly altered UI, especially during the early growth phase (Growth Phase I) as compared to the later growth phase (Growth Phase II). Temperature variability increased UI in rainfed production; an increase in the number of days above optimum temperature in Growth Phase I affected UI in minor irrigation; higher rainfall during Growth Phase I reduced UI in rainfed production; and higher rainfall variation reduced UI under all water regimes. Our findings suggest the importance of formulating localized climate‐smart adaptation policies and specific crop insurance programs for rainfed paddy production.

Spatiotemporal Variations in Fractional Vegetation Cover and Their Responses to Climatic Changes on the Qinghai–Tibet Plateau

The alpine vegetation of the Qinghai–Tibet Plateau (QTP) is extremely vulnerable and sensitive to climatic fluctuations, making it an ideal area to study the potential impacts of climate on vegetation dynamics. Fractional vegetation cover (FVC) is regarded as one of the key indicators in monitoring semiarid and arid ecosystems due to its sensitive responses to vegetation behavior under climatic changes. Although many studies have analyzed the responses of vegetation on the QTP to climatic change, limited information is available on the influence of climatic variables on FVC changes in this area. In this study, we used satellite images and meteorological data to investigate the spatiotemporal variations of FVC during the growing season (FVCGS) during 1998–2018 and evaluated the responses to changes in climatic variables. Results showed that FVCGS displayed an overall fluctuating rise of 0.01/10 a (p &lt; 0.01) over the study period. The FVCGS variation was spatially heterogeneous, with a general trend of greening in the northern and browning in the southern QTP. Obvious correlations were observed between the average FVC, average temperature, and total precipitation of the growing season, with precipitation being the primary controlling factor for vegetation growth. Some regions in the northwestern and northeastern QTP showed greening trends due to the positive influence of precipitation. Some areas in the southwestern QTP experienced browning trends due to water shortages caused, probably, by the weakening of the Indian monsoon. Browning in the southeastern parts was likely caused by drought and permafrost degradation resulting from high temperature. The inconsistent trend of vegetation change on the QTP is relatively high considering the continuous warming and changing atmospheric circulation patterns. FVC in most regions of the QTP has 0–1 month temporal responses to precipitation and temperature. Moreover, the one-month lagged effects of temperature and precipitation had a greater influence on steppe and desert vegetation than on other vegetation types. This research provides new perspectives for understanding the QTP vegetation response to climatic changes and a basis for making reasonable vegetation conservation and management policies.